Collaborative Research: Examining the Development of Student Reasoning Skills Through Scaffolded Physics Instruction

这是一个合作项目，涉及北达科他州州立大学(1431857)、缅因州大学(1431940)、宾夕法尼亚州立大学大阿勒格尼(1431541)、华盛顿大学(1432765)和西华盛顿大学(1432052)。除了帮助学生学习基础物理内容外，大学级物理课程最重要的目标之一是帮助学生学习如何推理。要在STEM领域取得成功，学生必须能够建立导致预测、推理或结论的多步骤解释。经验丰富的物理教师认识到，这对许多学生来说是困难的。虽然已经对学生如何理解物理中的个别概念进行了大量的研究，但到目前为止，关于学生如何学习将想法联系在一起的研究还很少。在许多情况下，教育干预被证明对最优秀的学生帮助最大，从而扩大了成绩优异和成绩低下的学生之间的差距。学生潜在推理能力的差异可能解释了这种影响的差异。该项目的成果既有可能缩小这种差距，也有可能增加STEM学科中高危学生的留存率。由于这是一种新的研究途径，本项目的主要目标之一是开发工具和方法来可靠地测量学生推理，并在不同的学生群体中测试这些工具。这些工具将与其他研究人员共享，以便更广泛地应用于STEM课程中学生推理能力发展的研究。尽管从不同的研究角度持续关注推理和问题解决，但对学生如何在解决定性物理问题中构建推理链知之甚少。由于推理在发展和应用科学知识方面的重要性，以及相对缺乏经验和理论资源来理解和评估这种推理的发展，有必要在这一领域进行更多的研究。这一探索性项目的核心是开发新的工具和方法，将对物理学的概念理解与有效应用这种理解所需的推理能力分开。该项目的具体目标是(1)开发能够可靠地测量学生推理的工具，以及(2)使用这些工具来调查大学物理课程中学生推理的发展。调查人员将同时开发和改进工具，并产生关于学生在物理推理中的新知识，包括确定促进或抑制产出式推理方法应用的因素和教学环境。研究人员将采用三种相辅相成的策略：(1)收集和分析从许多学生那里获得的单一时刻的快照数据(例如，对考试问题的书面回答)；(2)比较在不同情况下获得的快照数据的对照实验；以及(3)收集和分析来自学生访谈和课堂上通过材料工作的学生小组的视频数据。

This is a collaborative project involving North Dakota State University (Award DUE-1431857), the University of Maine (Award DUE-1431940), Penn State Greater Allegheny (Award DUE-1431541), the University of Washington (Award DUE-1432765), and Western Washington University (Award DUE-1432052).In addition to helping students learn foundational physics content, one of the most important goals of a college-level physics course is to help students learn how to reason. To be successful in STEM fields, students must be able to build multi-step explanations leading to a prediction, an inference, or a conclusion. Experienced physics instructors recognize that this is difficult for many students. Although a great deal of research has been conducted on how students develop an understanding of individual concepts in physics, there has been little research to date on how students learn to chain ideas together. In many cases, instructional interventions have been shown to help the strongest students most, thereby widening the gap between high- and low-achieving students. Differences in students' underlying reasoning abilities might account for this disparity of impact. The outcomes of this project have the potential both to decrease such gaps and to increase the retention of at-risk students in STEM disciplines. Because this is a new avenue of research, one of the primary goals of this project is to develop tools and methods for the reliable measurement of student reasoning, and to test these tools with diverse student populations. These tools will be shared with other researchers so that they can be applied more widely in studies of the development of students' reasoning abilities in STEM courses.Despite a sustained focus on reasoning and problem solving from a variety of research perspectives, little is known about how students construct inferential reasoning chains in solving qualitative physics problems. Because of the importance of reasoning in developing and applying scientific knowledge, as well as the relative lack of empirical and theoretical resources for understanding and assessing the development of such reasoning, there is a need for more research in this area. Central to this exploratory project is the development of new instruments and methodologies for disentangling conceptual understanding of physics from the reasoning abilities required to apply that understanding productively. Specific objectives of the project are (1) to develop instruments capable of reliably measuring student reasoning and (2) to use those instruments to investigate the development of student reasoning in university physics courses. The investigators will concurrently pursue both the development and refinement of instruments and the generation of new knowledge about students' reasoning in physics, including the identification of factors and instructional circumstances that enhance or suppress the application of productive reasoning approaches. The investigators will employ three complementary strategies: (1) the collection and analysis of snapshot data obtained from many students at a single instant (e.g., written responses to exam questions), (2) controlled experiments involving comparisons of snapshot data obtained under different circumstances, and (3) the collection and analysis of video data from student interviews and from groups of students working through materials in class.